Abstract
Cloud computing combines different technologies to assist IT sector. In the cloud computing, management and distribution of resources are not easy. The main aim of cloud computing is to provide well-organized scheduling of resources for both cloud providers and users. The resource management includes the sharing of resources with multiple users. It becomes more complicated when done based on users demand. The main function of resource scheduling is to distribute the resources equally for user’s request. To perform resource scheduling, they require exact calculated user requests on all nodes involved in resource distribution process. This can be directly taken from total demanded resource requests. Thus, the efficiency of resource scheduling mainly depends on user request quality. It is more important to know what the most related works are and where the current study is pointing, to provide latest options that well denote today’s resource scheduling objectives. In this paper, we provide a detailed survey of current works in the literature to offer result for resource scheduling in cloud computing.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
A. Nahir, A. Orda and D. Raz “Resource Allocation and Management in Cloud Computing”, In the Proc. of IEEE, IFIP, pp. 1078–1084, 2015.
S. Mustafa, B. Nazir, A. Hayat, A. Khan and S. Madani “Resource management in cloud computing: Taxonomy, prospects, and challenges” Journal of Computers and Electrical Engineering, vol. 47, pp. 186–203, 2015.
NIST, definition of cloud computing, http://csrc.nist.gov/publications/drafts/800-145/Draft-SP-800-145_cloud-definition.pdf.
T. Chaabouni and M. Khemakhem “Resource Management based on Agent technology In Cloud Computing”, In the Proc. of IEEE, NOORIC, pp. 372–375, 2013.
S. Madni, M. Latiff, Y. Coulibaly and S. Abdulhamid “Resource Scheduling for Infrastructure as a Service (IaaS) in Cloud Computing: Challenges and Opportunities”, Journal of Network and Computer Application, vol. 68, pp. 173–200, 2016.
S. Singh and I. Chana “Cloud Resource Provisioning: Survey, Status and Future Research Directions”, Journal of Knowledge and Information Systems, Springer, vol. 49, issue 3, pp. 1005–1069, 2016.
S. Sujan and R. Kanniga Devi A Batch mode Dynamic Scheduling Scheme for Cloud computing”, In the Proc. of IEEE, GCCT, pp. 297–302, 2015.
Y. Chiang, Y. Ouyang, A. Cremers and L. Xu “A Load-Based Scheduling to Improve Performance in Cloud Systems”, In the Proc. of IEEE, IRC, pp. 52–59, 2017.
E. Nehru, I. Shyni and R. Balakrishnan “Auction Based Dynamic Resource Allocation in Cloud”, In the Proc. of IEEE, ICCPCT, pp. 1–4, 2016.
B.S. Murugan, V. Vasudevan and B. Ganeshpandi “Intelligent Scheduling System Using Agent Based Resource Allocation In Cloud”, In the Proc. of IEEE, ICEEOT, pp. 3031–3035, 2016.
A. Thomas, G. Krishnalal and V. P. Jagathy “Credit Based Scheduling Algorithm in Cloud Computing Environment”, Procedia Computer Science Journal, vol.46, pp. 913–920, 2015.
A.T. Saraswathi, Y. Kalaashri and Dr. S. Padmavathi “Dynamic Resource Allocation Scheme in Cloud Computing”, Procedia Computer Science Journal, vol. 47, pp. 30–36, 2015.
D. Tenepalli and N. Appini “Active Resource Provision in Cloud Computing Through Virtualization”, In the Proc. of IEEE, ICCIC, pp. 1–4, 2014.
Y. Choi and Y. Lim “A Framework for Optimizing Resource Allocation in Clouds”, In the Proc. of IEEE, CIA, pp. 10–14, 2015.
S. Ali and M. Alam “A Relative Study of Task Scheduling Algorithms in Cloud Computing Environment”, In the Proc. of IEEE, IC3I, pp. 105–111, 2016.
R. Raju, R. Babukarthik and D. Chandramohan “Minimizing the Makespan using Hybrid Algorithm for Cloud Computing,”, in Proc. of IEEE, IACC, pp. 957–962, 2013.
J. Liu, Y. Zhang, Y. Zhou, D. Zhang and H. Liu “Aggressive Resource Provisioning for Ensuring QoS in Virtualized Environments”, IEEE Transactions on Cloud Computing, vol. 3, no. 2, pp. 119–131, 2015.
S. Zaman and D. Grosu, “A Combinatorial Auction-based Mechanism for Dynamic VM Provisioning and Allocation in Clouds,” IEEE Transactions on Cloud Computing, vol. 1, no. 2, pp. 129–141, 2013.
Y. Hu, B. Deng and F. Peng “Autoscaling Prediction Models for Cloud Resource Provisioning”, In the Proc. of IEEE, ICCC, pp. 1364–1369, 2016.
A. Buhussain, R. Grande, and A. Boukerche “Elasticity Based Scheduling Heuristic Algorithm for Cloud Environments”, In the Proc. of IEEE, DS-RT, pp. 1–8, 2016.
S. Saxena and D. Saxena “EWSA: An Enriched Workflow Scheduling Algorithm in Cloud Computing”, in the Proc. of IEEE, ICCCS, 2015.
K. M. Sim, “Agent-based Cloud Computing”, IEEE Transactions on Services Computing, vol. 5, no. 4, pp. 564–577, 2012.
S. Jayanthi “Literature review: Dynamic Resource Allocation Mechanism in Cloud Computing Environment”, in Proc. of IEEE, ICECCE, pp. 279–281, 2014.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sohani, M., Jain, S.C. (2018). State-of-the-Art Survey on Cloud Computing Resource Scheduling Approaches. In: Perez, G., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-10-7386-1_53
Download citation
DOI: https://doi.org/10.1007/978-981-10-7386-1_53
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7385-4
Online ISBN: 978-981-10-7386-1
eBook Packages: EngineeringEngineering (R0)